Discovering gastronomic tourists’ profiles through artificial neural networks: Analysis, opinions and attitudes

Abstract

As the importance given by tourists to the different aspects of gastronomic tourism depends on their profiles, this research aims to determine the relationship between the social characteristics of these culinary tourists (such as gender, age, income, and educational level) and the relevance attributed by them to several opinions and attitudes related to gastronomic tourism. This research is based on field work through surveys filled in by culinary tourists with questions about perceptions and thoughts regarding gastronomic tourism both in general and in the particular case of Córdoba, a World Heritage Site in Southern Spain. Using artificial intelligence techniques as the Multilayer Perceptron, an artificial neural network is developed to estimate a ‘tourist profile’ based on inputs which are the pre-determined replies to the questionnaire. This technique is rarely used in surveys, especially in tourism sector. The model developed can assess the variations produced along the item valuation in every characteristic of the tourist profile. Thus, an increase in age implies more appreciation for dishes variety, its tasting at destination and willingness to return. Findings presented can be useful for professionals and entrepreneurs dedicated to culinary experiences and for public institutions which aim to promote gastronomic tourism at destination.